DO NO HARM: APPLYNG EQUITY AWARENESS IN DATA VISUALIZATION
What is it?
This guide and its associated toolkits focus on how data practitioners can approach their work through a lens of diversity, equity, and inclusion.
This guide and its associated toolkits focus on how data practitioners can approach their work through a lens of diversity, equity, and inclusion.
Who is it for?
The guide should be of interested to researchers, designer, analysts and communication/marketing specialists - any data practitioners really.
The guide should be of interested to researchers, designer, analysts and communication/marketing specialists - any data practitioners really.
What can it do?
For researchers and analysts to unlock the full potential of their data, they must apply an equitable lens to every step of the research process. Were the data collected responsibly, and do they accurately represent the communities surveyed? Do researchers allow for and incorporate community input? Does the final product consider equity and inclusion in its presentation? The answers to these questions will vary by project, and there is no one-size-fits-all approach. But for data practitioners to truly do no harm, they must build their work on a foundation of equity.
For researchers and analysts to unlock the full potential of their data, they must apply an equitable lens to every step of the research process. Were the data collected responsibly, and do they accurately represent the communities surveyed? Do researchers allow for and incorporate community input? Does the final product consider equity and inclusion in its presentation? The answers to these questions will vary by project, and there is no one-size-fits-all approach. But for data practitioners to truly do no harm, they must build their work on a foundation of equity.
Schwabish, J. & Feng, A. (2021, June 09). Do no harm: Applying Equity Awarness in data visualization. Urban Institute. Retrieved from https://www.urban.org/research/publication/do-no-harm-guide-applying-equity-awareness-data-visualization (accessed 28 January 2022).